I. Technical Field
This invention pertains to wireless telecommunications, and particularly the use of wireless communication over channels having multiple transmit and multiple receive antennas.
II. Related Art and Other Considerations
Wireless communication over channels having multiple transmit and multiple receive antennas has generated a great deal of interest over the last decade. Multiple-input and multiple-output (MIMO) is the use of multiple antennas at both transmitter and receiver to improve communication performance. Until recently, most MIMO research was focused on serving a single user. In the single-user MIMO (SU-MIMO) case, if perfect channel state information (CSI) is available at the transmitter and receiver, one can diagonalize the channel, thereby creating as many parallel, non-interfering, sub-channels as the minimum number of transmit and receive antennas. Rather surprisingly, in the SU-MIMO case, it was later shown that the same number of parallel channels can be created between the transmitter and receiver even if only statistics of the channels are known at the transmitter (assuming some rather mild conditions on the average rank of the downlink channels). A. Tulino, A. Lozano, and S. Verdu, “Capacity-Achieving Input Covariance for Single-User Multi-Antenna Channels”, IEEE Trans, on Wireless Communications, VOL. 5, NO. 3, March 2006; and I. E. Teletar, “Capacity of multi-antenna Gaussian channels,” Eur. Trans. Telecom, vol. 10, pp. 585-595, November 1999.
In a non-coordinated cellular system, the transmissions in different cells are formed independently. Hence, the transmission from one cell typically acts as unwanted interference to mobiles in other cells. Since each cell acts independently, each cell has no way of knowing how its transmission will impact the mobiles in other cells. With small to medium-sized cells, other-cell interference is a main factor limiting the performance of the cellular system. Particularly for mobiles near the cell edge, the other-cell interference is a main factor prohibiting the delivery of high data rate to these users.
On the other hand, a coordinated system with distributed antennas uses its knowledge of the propagation environment to control the mutual interference by jointly shaping the signals that are transmitted to all the users.
More recently, considerable work has been done in investigating the role of multiple antenna systems in multiuser wireless networks, and especially in the broadcast (downlink) and multiple-access (uplink) scenarios. It has been shown recently that dirty-paper coding in conjunction with linear precoding is capacity achieving for the downlink Gaussian broadcast channel. See, e.g., H. Weingarten, Y. Steinberg, S. Shamai, “The capacity region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel,” in IEEE Trans. Infor. Theory, vol. 52, September 2006; G. Caire and S. Shamai, “On the achievable throughput in multiantenna Gaussian broadcast channel,” IEEE Trans. Infor. Theory, vol. 49, July 2003; and W. Yu and 3. Cioffi, “Sum capacity of Gaussian vector broadcast channels,” in IEEE Trans. Inform. Theory. All these results rely on the assumption that the channel between every transmitting antenna and every mobile is known perfectly at the transmitter at every frequency.
Coherent coordination schemes that have been proposed recently include the following:
Linear beamforming See, e.g., P. Viswanath and D. Tse, “Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality,” IEEE Trans. Inform. Theory, vol. 49, no. 8, August 2003.
Linear beamforming with dirty-paper coding. See, e.g., G. Caire and S. Shamai, “On the achievable throughput in multiantenna Gaussian broadcast channel,” IEEE Trans. Infor. Theory, vol. 49, July 2003.
Zero-forcing beamforming See, e.g., M. Karakayali, G. Foschini, and R. Valenzuela, “Network coordination for spectrally efficient communication in cellular systems,” in IEEE Wireless Communication, August 2006.
Zero-forcing beamforming and dirty-paper coding. See, e.g., Kambiz Zangi and Dennis Hui, “Costa-Precoding and Zero-Forcing Linear Beamforming for Gaussian Broadcast Channels,” Ericsson Internal Report, BAE-07:002519, June 2007.
There is a formidable problem with existing coherent schemes (such as those listed above, for example) for coordinating the transmissions in a system equipped with distributed antenna infrastructures. The problem is that these coherent schemes require that the channel between every transmitting antenna and every mobile be known perfectly at the transmitter. Assuming a system with t number of distributed antennas, with m number of users to be served on a given transmission timing interval (TTI), f number of subcarriers, and r number of receive antennas per user, the network must acquire the exact value of t×m×f×r channel coefficients for each TTI (e.g., very one msec). Enabling the network to acquire this information might require considerable overhead and feedback from the mobiles to the network (especially in a frequency division duplex [FDD] system).